JupyterLab

Next-generation interactive computing environment for notebooks, code, and data

JupyterLab provides a flexible, extensible UI for notebooks, terminals, editors, and file browsing, supporting modern browsers and easy installation via conda, mamba, or pip.

Overview

Highlights

Modular UI with drag‑and‑drop layout for notebooks, terminals, and editors

Rich extension ecosystem via npm, PyPI, and conda

Native support for modern browsers (Firefox, Chrome, Safari)

Seamless upgrade path from JupyterLab 3 to 4 with back‑ported critical fixes

Pros

Highly extensible through public APIs
Unified interface replaces classic notebook
Cross‑platform installation via conda, mamba, pip
Active community and regular updates

Considerations

Requires Python environment setup
Large install size for full feature set
Extension development may need an npm build step
Version 3 no longer maintained beyond Dec 2024

Managed products teams compare with

When teams consider JupyterLab, these hosted platforms usually appear on the same shortlist.

COC

CoCalc

Collaborative cloud notebooks (Jupyter, LaTeX, SageMath) with real-time editing

Databricks Notebooks

Real-time collaborative notebooks for data & AI on Databricks

Deepnote

Collaborative data notebook for Python & SQL with real-time teamwork

Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.

Fit guide

Great for

Data scientists needing interactive notebooks with integrated tools
Researchers who want reproducible computational workflows
Developers building custom IDE‑like extensions
Teams requiring browser‑based collaborative environments

Not ideal when

Users seeking minimal lightweight CLI‑only tools
Environments without Python or Node.js support
Projects that require long‑term support for JupyterLab 3 after 2024
Systems with strict bandwidth constraints for large package installs

How teams use it

Exploratory data analysis

Run notebooks, visualize results, and edit scripts side‑by‑side for faster insight generation.

Teaching interactive courses

Provide students a browser‑based lab with notebooks and terminals, simplifying setup and ensuring a consistent environment.

Developing custom data‑science extensions

Use npm APIs to add new panels or widgets, creating a tailored UI for specific workflow needs.

Deploying reproducible research pipelines

Combine notebooks, scripts, and versioned files in one workspace to ensure reproducibility and easy sharing.

Tech snapshot

TypeScript87%

Python5%

CSS4%

JavaScript2%

Jupyter Notebook1%

Shell1%

Frequently asked questions

How do I install JupyterLab?

Use `conda install -c conda-forge jupyterlab`, `mamba install -c conda-forge jupyterlab`, or `pip install jupyterlab`.

What browsers are supported?

The latest versions of Firefox, Chrome, and Safari are known to work.

Do I need to enable a server extension for older Notebook versions?

Yes, for Notebook versions earlier than 5.3 run `jupyter serverextension enable --py jupyterlab --sys-prefix` after installation.

Is JupyterLab 3 still maintained?

Maintenance ended May 15 2024; critical fixes are back‑ported only until Dec 31 2024. Upgrade to JupyterLab 4 is recommended.

How can I add extensions?

Extensions can be installed from PyPI, conda, or directly via npm; prebuilt extensions require no additional build step.

Project at a glance

Active

Visit site View repo

Stars: 14,987
Watchers: 14,987
Forks: 3,882

Repo age9 years old

Last commit4 hours ago

Primary languageTypeScript

Last synced 3 hours ago